#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Copyright 2020 Huawei Technologies Co., Ltd

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
from __future__ import print_function
from setuptools import setup
import os
import shutil

check_fpath = os.path.join("_swig_ascendfaiss.so")
if not os.path.exists(check_fpath):
    print("Could not find {}".format(check_fpath))

# make the ascendfaiss python package dir
shutil.rmtree("ascendfaiss", ignore_errors=True)
os.mkdir("ascendfaiss")
shutil.copyfile("ascendfaiss.py", "ascendfaiss/__init__.py")
shutil.copyfile("swig_ascendfaiss.py", "ascendfaiss/swig_ascendfaiss.py")
shutil.copyfile("_swig_ascendfaiss.so", "ascendfaiss/_swig_ascendfaiss.so")

long_description = """
Ascendfaiss is a library for efficient similarity search and clustering of
dense vectors on Ascend.
"""
setup(
    name='ascendfaiss',
    version='1.0.0',
    description='A library for efficient similarity search and clustering of \
        dense vectors',
    long_description=long_description,
    url='https://www.huawei.com',
    author='Huawei',
    author_email='',
    license='MIT',
    keywords='search nearest neighbors',

    install_requires=['numpy'],
    packages=['ascendfaiss'],
    package_data={
        'ascendfaiss': ['*.so'],
    },
)
